TST(string dtype): Resolve replace xfails #60659
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rhshadrach
added
Testing
| # TODO(infer_string): both string columns get cast to object, | ||
| # while only needed for column A | ||
| expected_df2 = DataFrame({"A": [1], "B": ["1"]}, dtype=object) |
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I think this behavior was correct - we get object dtype here because we are trying to replace string values with integer values. If we were to make the result a string dtype, then that would be introducing value-specific behavior.
| else: | ||
| expected_df2 = DataFrame({"A": Series([1], dtype=object), "B": ["1"]}) |
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This behavior looks incorrect to me, B here should also be object dtype. I think we can raise an issue (this is independent of infer_strings) if others agree.
| expected_df1 = DataFrame({"A": [1], "B": [1]}, dtype=object) | ||
| result_df1 = df1.replace(to_replace="0", value=1, regex=regex) | ||
| # When value is an integer, coerce result to object. | ||
| # When value is a string, infer the correct string dtype. |
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Are we sure we want to coerce to string instead of raising? The object case makes sense I'm just not as sure onn the string side if we should be implicitly casting like that
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Not sure I understand. When infer_string=True, the input DataFrame is str dtype. Then when we go to replace "0" with value="1", certainly we want the result to still be str dtype, no?
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Yea I think that makes sense, but I'm not as sure when the target value is a non-string, i.e. replace(..., value=1)
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When the target value is a non-string, we coerce to object dtype in order to hold both integers and strings. What are you not sure about?
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Sorry I was just misreading the comment - I think this is good
doc/source/whatsnew/vX.X.X.rstfile if fixing a bug or adding a new feature.